Data Engineer

About the role

Data & Analytics Engineer Digital Transformation Practice Location: Remote — United States | Type: FTE or Contract (1099/C2C) | Duration: 18-month+ engagements (FTE ongoing) About Aberdeen Advisors Aberdeen Advisors is a boutique managed services and C-level digital strategy firm. We embed with clients across healthcare, financial services, and technology to drive real transformation—not slide decks. Our data practice is growing fast, and we’re looking for engineers who want to build things that matter. The Role This is a client-facing, hands-on data engineering role. You’ll join multi-disciplinary transformation engagements and own the full data lifecycle—from raw ingestion to polished, decision-ready visualizations. The clients you’ll support range from CIOs to finance teams, and your job is to turn messy, siloed data into clarity. You don’t need to check every box below on day one. What you must have is strong Python fundamentals, solid debugging instincts, and a genuine hunger to learn. The rest is teachable. What You’ll Do Evaluate client data sources and determine optimal ingestion strategies via APIs, connectors, and direct exports. Land and structure data into lakehouses using Medallion architecture (Bronze → Silver → Gold). Build and validate transformation pipelines in Python/PySpark via Jupyter Notebooks. Apply ML where it adds value—forecasting, anomaly detection, and narrative generation. Deliver dynamic, role-specific dashboards in Power BI (preferred) or Tableau; validate visuals against source systems with rigor. Integrate LLM capabilities (OpenAI) for summaries, embeddings, and AI-generated narratives. Contribute to agentic AI workflows as the practice scales. What We’re Looking For Must-Haves Python proficiency: You can write it, read it, and debug it confidently under real-world conditions. Problem-solving instincts: You don’t give up when something breaks; you dig in and figure it out. Clear communication: Ability to translate technical concepts clearly to non-technical stakeholders at all levels. Intellectual curiosity: A genuine bias toward action and a hunger to learn in a fast-moving practice. Nice-to-Haves (learnable on the job) Data lake/lakehouse concepts—Delta tables, Microsoft Fabric, Databricks, etc. Orchestration tools such as Airflow or Microsoft Fabric. Power BI or Tableau experience. ML fundamentals—classification, regression, clustering. LLM/API integration experience. Basic awareness of agentic AI frameworks and MCP tooling (Claude Code, VS Code agents, etc.). Why This Role Stands Out You won’t be siloed. Every engagement exposes you to a new domain—healthcare, pharma, finance—and a new source system. Over time, that cross-domain fluency becomes a career asset that’s genuinely hard to replicate. You’ll also work at the intersection of traditional data engineering and emerging AI—a rare combination at the practitioner level that positions you well for where the market is heading. Engagement Details Employment Type: Full-Time Employee (FTE) or Contract (1099/C2C)—we’re open to both. Duration: 18-month+ engagements (FTE ongoing). Compensation: Commensurate with experience. Location: Fully remote. Aberdeen Advisors is an equal opportunity employer. We evaluate candidates on ability and potential, not pedigree.